Impact of pest management practices on the frequency of insecticide resistance alleles in Bemisia tabaci (Hemiptera: Aleyrodidae) populations in three countries of West Africa

HAL Id: hal-01916784

https://hal.archives-ouvertes.fr/hal-01916784

HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Impact of pest management practices on the frequency

of insecticide resistance alleles in Bemisia tabaci

(Hemiptera: Aleyrodidae) populations in three countries

of West Africa

Olivier Gnankine, Omer Hema, Moussa Namountougou, Laurence Mouton,

Fabrice Vavre

To cite this version:

Olivier Gnankine, Omer Hema, Moussa Namountougou, Laurence Mouton, Fabrice Vavre. Impact of pest management practices on the frequency of insecticide resistance alleles in Bemisia tabaci (Hemiptera: Aleyrodidae) populations in three countries of West Africa. Crop Protection, Elsevier, 2018, 104, pp.86 - 91. �10.1016/j.cropro.2017.10.020�. �hal-01916784�

1

Impact of pest management practices on the frequency of insecticide

resistance alleles in Bemisia tabaci (Hemiptera: Aleyrodidae) populations in

three countries of West Africa.

5

Olivier Gnankiné a, HemaOmerb, Moussa Namountougou c, Laurence Moutond and 6

Fabrice Vavred 7

8

a Laboratoire d’Entomologie Appliquée, Université de Ouaga I Pr Joseph KI-ZERBO, 9

Burkina Faso. 10

b Institut de l’Environnement et de Recherches Agricoles, BP 390 Bobo-Dioulasso, Burkina 11

Faso 12

c Université Nazi Boni de Bobo-Dioulasso, Burkina Faso 13

d Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie 14

Evolutive UMR5558, F-69622 Villeurbanne, France. 15

16 17

* Corresponding author: Laboratoire d’Entomologie Fondamentale et Appliquée, 18

Departement de Biologie et Physiologie Animales, Université de Ouagadougou, 03 BP 7021 19

Ouagadougou 03, Email : olivier.gnankine@univ-ouaga.bf; olgnankine@hotmail.com 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

2

ABSTRACT

35 36

In West Africa, the use of organophospates and pyrethroids insecticides to control cotton 37

pests has led to the evolution of resistance in field populations of Bemisia tabaci Gennadius. 38

Three pest management programs have been commonly recommended: the Conventional 39

Program (CP) where 6 treatments are applied, the use of Bt cotton plants for which only 2 40

applications of neonicotinoids are required and that has been adopted in many countries, and a 41

biological program (BP) without any chemical treatment. The present study aims to determine 42

the influence of these practices on the frequency of mutations that confer resistance to 43

pyrethroids (mutation L925I in the para-type voltage-gated sodium channel gene) and 44

organophosphates (mutation F331W in the acetylcholinesterase enzyme ace1: allele Ace1R) in 45

B. tabaci populations using Bt cotton and CP areas in Pô and Saria (Burkina Faso), CP and

46

BP areas in Kandi (Benin) and only CP areas in Tové and Infa (Togo). All individuals 47

sampled belonged to the MED (biotypes MED-Q1) and Africa Silver Leafing (ASL) species. 48

MED-Q1 was found in sympatry with ASL in Burkina Faso both on CP and Bt cotton areas at 49

variable frequencies. In Togo and Benin, only ASL was found, except in Tové where MED-50

Q1 was also detected, but at low frequency. Frequencies of mutations that confer resistance 51

varied between localities and species but we did not find any strong evidence of a relationship 52

between the pest management program and these frequencies except for the allele Ace1R in 53

Burkina Faso for which the frequencies decrease when chemical applications are reduced. 54

This study provides valuable information for the development of efficient integrated pest 55

management programs. 56

Key words: Pest management programs, insecticides, kdr, Ace1R, Bemisia tabaci. 57

58 59 60

3 1. Introduction

62 63

In western Africa, cotton is an economically important crop providing substantial 64

incomes for farmers. However, the cotton plant is attacked by key pests including the cotton 65

bollworm, Helicoverpa armigera (Lepidoptera: Noctuidae) and the whitefly Bemisia tabaci 66

Gennadius (Hemiptera: Aleyrodidae). Three main spraying programs are recommended to 67

control these pests in many countries of West Africa. They include the Conventional Cotton 68

program (CP), the Biological Program (BP) and the transgenic Bt cotton program (Bt Cotton). 69

The CP is based on calendar-based applications of insecticides belonging to pyrethroids, 70

organophosphates and neonicotinoids families separately or as a mixture (Gnankiné et al., 71

2013a; Silvie et al., 2013). They are applied with temporal rotations during the whole cotton 72

season (from May to October). The repeated use of such insecticides have imposed strong 73

selection pressures on target pests’ populations, resulting in the evolution of field resistances 74

(Houndeté et al., 2010). Over $60 millions of chemicals were spent for chemical pests control 75

in Burkina Faso (Greenplate et al., 2006). The BP relies on the use of biopesticides and 76

natural fertilizers without utilization of any chemical. The Bt cotton program uses Bt (Bacillus 77

thuringiensis) transgenic cotton plants that express two crystal toxins (Cry1Ac and Cry2Ab)

78

that target some major lepidopteran pests but are harmless to vertebrates and most other 79

organisms (Mendelsohn et al., 2003; Sanahuja et al., 2011; Pardo-Lopez et al., 2013). In this 80

program, only neonicotinoids are used at the end of the cotton phenological stages (Héma et 81

al., 2009). It was initiated in 2008 in West Africa but only in Burkina Faso. In 2016, the 82

Burkina Faso government suspended the use of Bt technology due to the quality of cotton 83

fiber which is shorter than the fiber of conventional cotton. 84

One of major threat to cotton plant remains the whitefly B. tabaci. It causes damages directly 85

through phloem feeding and indirectly through the transmission of plant viruses. B. tabaci is a 86

4 complex of cryptic species whose taxonomy is still not entirely resolved. Based on the current 87

consensus, B. tabaci is mostly represented by the MED species in western Africa, even 88

though AnSL species can also be found (Gnankiné et al., 2013b; Gnankiné et al., 2013c). 89

Within the MED species, different biotypes are encountered including MED-Q1, MED-Q3 90

and ASL. Actually, recent analyses suggest that MED-Q1 and ASL do not hybridize in the 91

field and that ASL is thus a different species (Mouton et al., 2015). Interestingly, these 92

species/biotypes differ in terms of host plants range and insecticide resistance traits. 93

Generally, MED-Q1 is predominant in cotton areas and sometimes found in sympatry with 94

ASL on vegetables crops (Gnankiné et al., 2013b). It is also associated with higher levels of 95

resistance to some insecticides as pyrethroids, organophosphates and neonicotinoids 96

(Gnankiné et al., 2013a). In B. tabaci, two mutations in the para-type voltage-gated sodium 97

channel gene, L925I and T929V, and one mutation in the acetylcholinesterase enzyme ace1 98

(F331W: allele Ace1R) confer resistance to pyrethroids and organophosphates, respectively 99

(Roditakis et al., 2006; Alon et al., 2008; Tsagkarakou et al., 2009). Recent studies showed 100

that the Ace1R was found in both MED-Q1 and ASL but, while this resistant allele was almost 101

fixed in MED-Q1 (0.99), its frequency was 0.59 in ASL (Mouton et al., 2015). In addition, 102

while the L925I mutation in the sodium channel gene is almost fixed in MED-Q1 populations, 103

it is rarely detected in ASL. The T929V was never found in B. tabaci populations from West 104

Africa (Mouton et al., 2015). The objectives of the present study were to perform a first 105

analysis of the impact of the agricultural practices on the B. tabaci biotypes/species 106

composition and diversity, and the frequencies of alleles that confer resistance to pyrethroids 107

and organophosphates. Sampling was performed in three countries of Western Africa: 108

Burkina Faso, Benin and Togo. 109

110

5 2. Materials and methods

113

2.1 Management of cotton pests 114

Three pest control programs are recommended in West African countries:

115

(i) The Conventional Program (CP) is based on two to four treatments with pyrethroids (PY) 116

plus organophosphates (OP) and 2 other treatments with neonicotinoids (see table 1 for 117

details). 118

(ii) The Biological control Program (BP) does not use chemicals for plant protection. Farmers

119

worked under the supervision of technicians from the Beninese Organization for Organic

120

Farming Promotion (OBEPAP) who participated in the implementation and the survey of

121

good agricultural practices on organic cotton.

122

(iii) The transgenic cotton program (Bt Cotton). In this program, pesticides belonging to OP 123

and PYR are not used. Only neonicotinoids are used at boll opening stage to control sucking 124

pests. In this case, farmers worked under the supervision of technicians from societies of 125

textile fibers in Burkina Faso. 126

127

2.2 B. tabaci sampling 128

Sampling was performed in october and november between 2009 and 2015 in three countries 129

of Western Africa: Burkina Faso, Benin and Togo (Figure 1, Table 2). In Burkina Faso, 130

whiteflies were collected randomly in two localities, Pô in 2013 and Saria in 2015, from Bt 131

cotton and CP fields. In Pô, Bt cotton represented 90% of the sampled fields while in Saria it 132

represented 15%. In Benin, sampling was done at Kandi in 2009 in CP and BP areas (BP 133

represent around 10% of areas). In Togo, collection was done randomly in two sites in 2009, 134

Infa and Tové, where only CP is used. The collected adult whiteflies were stored in ethanol 135

6 95%. The origin of the samples (location) and the number of individuals are summarized in 136 Table 2. 137 138 2.3 Molecular analysis 139 DNA extraction 140

For each individual, total DNA was extracted in 25 μl of an extraction buffer containing 141

50 mM KCl, 10 mM Tris-base pH 8, 0.45% Nonidet P-40, 0.45% Tween 20 and 50 mg/ml 142

proteinase K. After 3 h at 65°C, samples were incubated at 100°C for 15 min. Pure water 143

(35 μl) was then added to the extract. 144

Identification of B. tabaci 145

Species/biotypes were identified using the Polymerase Chain Reaction-Random Fragment 146

Length Polymorphism (PCR-RFLP) diagnostic assay based on the mitochondrial cytochrome 147

oxidase 1 gene sequence (mtCO1) described in Henri et al. (2013). This technique allows 148

discriminating the species/biotypes present in West Africa (Gnankiné et al., 2013b). 149

Identification of susceptible and resistant alleles of the sodium channel and the 150

acetylcholinesterase ace1 genes 151

Resistant and susceptible alleles in the para-type voltage-gated sodium channel and ace1 152

genes were identified using the diagnostic assays developed by Tsagkarakou et al. (2009). 153

Briefly, ace1-susceptible (F331) and -resistant (W331) alleles, as well as susceptible (L925) 154

and resistant (I925) para-type voltage-gated sodium channel alleles were detected using PCR-155

RFLP (Tsagkarakou et al. 2009). Some PCR products were sequenced for each susceptible 156

and resistant allele and each country. We never found the T929V mutation in the sequences. 157

The frequencies of kdr and ace-1R mutations were calculated according to the formula 158

p= n♂(R)+2n♀(RR)+n♀(RS)/n♂+2n♀where RR was the number of homozygotes, RS the

159

number of heterozygotes and n the size of specimens analysed. 160

7 2.4 Statistical analyses

162

Statistical analysis were performed using the R statistical software ( http://www.R-163

project.org). The effects of the pest management practices on the proportions of B. tabaci 164

composition and the frequencies of resistance alleles were tested by using Fisher’s exact tests. 165 166 167 3. Results 168 169

3.1 Geographic distribution of biotypes 170

All the 170 B. tabaci individuals collected in 5 localities in Burkina Faso, Benin and Togo 171

belonged to MED-Q1 or ASL(Table 2). In Togo and Benin, only ASL was found (except one 172

MED-Q1 individual in Tové), while in Burkina Faso, MED-Q1 and ASL were found in 173

sympatry at variable frequencies: depending on the locality, it was either ASL or MED-Q1 174

that predominated. In Pô, the frequency of ASL reached more than 80% whatever the control 175

strategy (CP or Cotton Bt). In Saria, MED-Q1 was more common than ASL, but their relative 176

frequencies depended on the management program: on CP areas, 93 % of individuals 177

belonged to MED-Q1 while only 57% of whiteflies were MED-Q1 on Bt Cotton fields (Fisher 178

exact test, p<0.005). 179

180 181

3.2 Frequency of the L925I mutation 182

183 184

For the para-type voltage-gated sodium channel gene, we studied the frequency of the L925I 185

mutation that correspond to the allele called r1 by Alon et al. (2008). We found high 186

variations depending on the country (Fisher exact test, p<0.0005). Indeed, in Burkina Faso, r1 187

8 was fixed for both MED-Q1 and ASL in the two localities (Table 3). In Benin, this allele has 188

not been found (Table 4). In Togo, its frequency varied between 0.5 and 0.75 (Table 5). 189

190 191

3.3 Frequency of the Ace-1R allele 192

193 194

For the acetylcholinesterase gene, we studied the presence of the F331W mutation (R allele). 195

Globally, the frequency of this allele was more homogeneous among countries than for the 196

L925I mutation and ranged between 0.71 and 1 (Fisher exact test, p=0.08). In Togo, this 197

frequency did not differ between the two localities, Infa and Tové (Table 5; Fisher exact test, 198

p=0.1). In Benin, where sampling was performed in only one locality, the frequency of R 199

varied between 0.7 and 0.9 but did not significantly differ between the fields that were treated 200

either with BP or CP program (Table 4; Fisher exact test, p=0.49). 201

In Burkina Faso, the frequency of the resistant allele changed in the two localities according 202

to the treatment: it was lower in Bt Cotton areas than in CP fields (Table 3; Fisher exact test, 203

p=0.003 for Pô and p<0.0005 for Saria). In the two localities, R was fixed in MED-Q1 in the 204

CP fields while it had a frequency of 0.5 and 0.875 in Pô and Saria respectively in Bt areas 205

(Fisher exact test, p<0.0005). For ASL, differences were not so important and not statistically 206

significant (Fisher exact test, p>0.05) with a range of frequencies between 0.91 and 1 for CP 207

fields and 0.71 - 0.83 for Bt cotton fields. 208 209 210 211 212 213 214 215 216 217 218 219 220 221

9 223

224

In this paper, we present the distribution of B. tabaci biotypes/species and the frequencies of 225

the mutations in the para sodium channel gene (kdr) and in the Acetylcholinesterase gene 226

(ace-1R) associated with resistance to Pyrethroids and Organophosphates respectively of the 227

pest B. tabaci in 3 countries of Western Africa in connection with the pest management 228

programs. 229

Our results confirmed the diversity of B. tabaci biotypes on cotton in these countries. As 230

previously described by Gueguen et al. (2010) and Gnankiné et al. (2013b), MED-Q1 and 231

ASL were detected in Burkina Faso, frequently in the same areas. Despite this sympatry, 232

population genetics analyses on microsatellite markers suggested that MED-Q1 and ASL do 233

not hybridize in the field (Mouton et al. 2015). It was also showed that they do not share 234

insecticide resistance alleles. ASL previously classified in MED-species might thus be 235

considered now as putative species (Mouton et al. 2015). 236

In the current study, the L925I mutation was fixed in MED-Q1 and ASL individuals in 237

Burkina Faso. Regarding ASL, this is in sharp contrast with the situation observed in 2009 238

and 2010, as this mutation only reached 0.02 at that time in the western part of Burkina Faso 239

(Mouton et al. 2015). This is also in contrast with the situation found in Benin, where this 240

resistant allele was not found, whatever the control program. Finally, the situation is 241

intermediate in Togo where the frequencies varied between 0.5-0.75 in CP or BP programs. 242

The fixation of this L925I mutation might be explained by a high selection pressure due to the 243

repetitive pyrethroids treatments applied in western Africa particularly on cotton and 244

vegetables (Gnankiné et al., 2007; Ahouangninou et al., 2011; Gnankiné et al. 2013b). 245

The management of the resistance mutations in the para-type voltage-gated sodium channel 246

gene, L925I but also T929V, seems to be difficult as they prove to be persistent even without 247

10 selection in laboratory, suggesting a low fitness cost (Roditakis et al., 2006). This low fitness 248

cost was confirmed by Alon et al. (2006) where no departures from Hardy–Weinberg 249

equilibrium were observed when the frequency of resistant genotypes was investigated in B. 250

tabaci populations reared without any insecticide selection for many years. Accordingly, we

251

could not detect any impact of the control program on the frequency of these resistance 252

mutations. 253

For the F331W mutation (ace1 gene), the frequencies of resistant alleles were very variable. 254

According to Mouton et al. (2015), the frequencies of the F331W mutation in the ace1 gene in 255

individuals from Burkina Faso were 0.98 and 0.59 for MED-Q1 and ASL, respectively. Our 256

data indicated that the frequency of resistance may be lower in individuals sampled in fields 257

using Bt cotton strategy than in the fields using CP. This effect was more pronounced in 258

MED-Q1 than ASL, and also more pronounced in Pô than in Saria. The high frequencies 259

observed in Saria could be due to the number of applications done for the pest control. Indeed, 260

near Saria, many farmers cultivate vegetables that are systematically treated with pyrethroids 261

and Organophosphates. On the contrary, in Pô, no vegetables were cultivated and the 262

insecticide pressure was low. Moreover, a drastic lack of resistant homozygous in the Bt 263

cottonfields is consistent with the hypothesis of a high fitness cost associated with the F331W 264

mutation in this species. As 90% of the zone was using Bt in Pô, while it was only 15% in 265

Saria, the refuge zone without treatment is thus much more important in Pô, which could 266

allow a more rapid counter-selection of resistance alleles without treatment. On the other 267

hand, we could not detect any effect of the control program in Benin (CP vs. BP). This may 268

be explained by the fact that only 10% of the surface were cultivated using BP program. In 269

Togo, we did not detect any significant difference in the mutation frequencies in the two areas 270

but they were under the same insecticide pressure. 271

11 high frequencies of the two mutations in individuals insects conferring a multiple resistance. 273

Indeed, detoxifying enzymes such as esterases, glutathione S-transferases, and cytochrome 274

P450-dependent monooxygenases are involved in resistance to numerous insecticide classes 275

(Alon et al., 2008; Rauch and Nauen , 2003; Ma W et al., 2010). 276

In conclusion, our results suggest that different control programs may alter the frequency of 277

resistance alleles. However, the counter-selection of resistance alleles may depend on the one 278

hand on the fitness cost associated with resistance, and the other hand to the relative surface 279

of untreated areas. This clearly advocates for a better integration of control measures against 280

B. tabaci across the different host crops.

281 282 283 Acknowledgments 284 285

The authors are grateful to the following institute for the samples collection and the technical 286

assistance from Inera and University of Lomé. 287 288 289 290 291 292 293 294 295

12 296

297

References

Ahouangninou C, F.B. and M.T., 2011. Évaluation des risques sanitaires et environnementaux 299

des pratiques phytosanitaires des producteurs maraîchers dans la commune rurale de 300

Tori-Bossito (Sud-Bénin). Cah. Agric. 20, 216–222. 301

Alon, M., Alon, F., Nauen, R., Morin, S., 2008. Organophosphates ’ resistance in the B-302

biotype of Bemisia tabaci ( Hemiptera : Aleyrodidae ) is associated with a point mutation 303

in an ace1 -type acetylcholinesterase and overexpression of carboxylesterase 38, 940– 304

949. doi:10.1016/j.ibmb.2008.07.007 305

Alon, M., Benting, J., Lueke, B., Ponge, T., Alon, F., Morin, S., 2006. Multiple origins of 306

pyrethroid resistance in sympatric biotypes of Bemisia tabaci (Hemiptera: Aleyrodidae). 307

Insect Biochem. Mol. Biol. 36, 71–79. doi:10.1016/j.ibmb.2005.10.007 308

Gnankiné, O., Bassolé, I.H.N., Chandre, F., Glitho, I., Akogbeto, M., Dabiré, R.K., Martin, 309

T., 2013a. Insecticide resistance in Bemisia tabaci Gennadius (Homoptera: Aleyrodidae) 310

and Anopheles gambiae Giles (Diptera: Culicidae) could compromise the sustainability 311

of malaria vector control strategies in West Africa. Acta Trop. 128. 312

doi:10.1016/j.actatropica.2013.06.004 313

Gnankiné, O., Mouton, L., Henri, H., Terraz, G., Houndeté, T., Martin, T., Vavre, F., Fleury, 314

F., 2013b. Distribution of Bemisia tabaci (Homoptera: Aleyrodidae) biotypes and their 315

associated symbiotic bacteria on host plants in West Africa. Insect Conserv. Divers. 6. 316

doi:10.1111/j.1752-4598.2012.00206.x 317

Gnankiné, O., Mouton, L., Savadogo, A., Martin, T., Sanon, A., Dabire, R.K., Vavre, F., 318

Fleury, F., 2013c. Biotype status and resistance to neonicotinoids and carbosulfan in 319

Bemisia tabaci (Hemiptera: Aleyrodidae) in Burkina Faso, West Africa. Int. J. Pest 320

Manag. 59. doi:10.1080/09670874.2013.771806 321

13 insecticides et dynamique des populations de Bemisia tabaci Gennadius en culture

323

cotonnière au Burkina Faso. Cah. Agric. 16. 324

Gueguen, G., Vavre, F., Gnankine, O., Peterschmitt, M., Charif, D., Chiel, E., Gottlieb, Y., 325

Ghanim, M., Zchori-Fein, E., Fleury, F., 2010. Endosymbiont metacommunities, 326

mtDNA diversity and the evolution of the Bemisia tabaci (Hemiptera: Aleyrodidae) 327

species complex. Mol. Ecol. 19, 4365–4376. doi:10.1111/j.1365-294X.2010.04775.x 328

Héma, O., Somé, H.N., Traoré, O., Greenplate, J., Abdennadher, M., 2009. Efficacy of 329

transgenic cotton plant containing the Cry1Ac and Cry2Ab genes of Bacillus 330

thuringiensis against Helicoverpa armigera and Syllepte derogata in cotton cultivation in 331

Burkina Faso. Crop Prot. 28, 205–214. doi:10.1016/j.cropro.2008.09.014 332

Henri, H., Terraz, G., Gnankiné, O., Fleury, F., Mouton, L., 2013. Molecular characterization 333

of genetic diversity within the Africa/Middle East/Asia Minor and Sub-Saharan African 334

groups of the Bemisia tabaci species complex. Int. J. pest Manag. 59, 329–338. 335

doi:10.1080/09670874.2013.869374 336

Houndeté, T. A., Kétoh, G.K., Hema, O.S. a, Brévault, T., Glitho, I. A., Martin, T., 2010. 337

Insecticide resistance in field populations of Bemisia tabaci (Hemiptera: Aleyrodidae) in 338

West Africa. Pest Manag. Sci. 66, 1181–1185. doi:10.1002/ps.2008 339

Ma W, Li X, Dennehy TJ, Lei C, Wang M, D.B. and N.R., 2010. Pyriproxyfen resistance of 340

Bemisia tabaci (Homoptera: Aleyrodidae) biotype B: metabolic mechanism. J. Econ 341

Entomol 103, 158–165. 342

Mike Mendelsohn, Kough1, J., Vaituzis, Z., Keith, M., 2003. Are Bt crops safe? Nat. 343

Biotechnol. 21, 1003–1009. doi:10.1038/nbt0903-1003 344

Mouton, L., Gnankiné, O., Henri, H., Terraz, G., Ketoh, G., Martin, T., Fleury, F., Vavre, F., 345

2015. Detection of genetically isolated entities within the Mediterranean species of 346

Bemisia tabaci: New insights into the systematics of this worldwide pest. Pest Manag. 347

Sci. 71. doi:10.1002/ps.3834 348

14 Pardo-Lopez, L., Soberon, M., Bravo Alejandra, 2013. Bacillus thuringiensis insecticidal 349

three-domain Cry toxins: mode of action, insect resistance and consequences for crop 350

protection. FEMS, Microbiol. Rev. 37, 3–22. doi:10.1111/j.1574-6976.2012.00341.x 351

Rauch N and Nauen R, I. (2003)., 2003. Identification of biochemical markers linked to 352

neonicotinoid cross resistance in Bemisia tabaci (Hemiptera: Aleyrodidae). Arch Insect 353

Biochem Physiol 54, 165–176. 354

Roditakis, E., Tsagkarakou, A., Vontas, J., 2006. Identification of mutations in the para 355

sodium channel of Bemisia tabaci from Crete, associated with resistance to pyrethroids. 356

Pestic. Biochem. Physiol. 85, 161–166. doi:10.1016/j.pestbp.2005.11.007 357

Sanahuja, G., Banakar, R., Twyman, R.M., Capell, T., Christou, P., 2011. Bacillus 358

thuringiensis : a century of research , development and commercial applications 283– 359

300. doi:10.1111/j.1467-7652.2011.00595.x 360

Silvie, J.P., Renou, A., Vodounnon, S., Bonni, G., Obayomi, M., Héma, O., Prudent, P., 361

Sorèze, J., Ochou, G., Togola, M., 2013. Threshold-based interventions for cotton pest 362

control in West Africa : What ’ s up 10 years later ? Crop Prot. 43, 157–165. 363

Tsagkarakou, A., Nikou, D., Roditakis, E., Sharvit, M., Morin, S., Vontas, J., 2009. Molecular 364

diagnostics for detecting pyrethroid and organophosphate resistance mutations in the Q 365

biotype of the whitefly Bemisia tabaci (Hemiptera: Aleyrodidae). Pestic. Biochem. 366

Physiol. 94, 49–54. doi:10.1016/j.pestbp.2009.03.002 367

Vitale, J., Glick, H., Greenplate, J., 2006. The Economic Impacts of Monsanto’s Paper, 368

Bollgard II in West Africa: Emprirical Evidence from Burkina Faso, in: 10th ICABR 369

Conference, Ravello, Italy. 370